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How to leverage AI in industrial sector and IoT

Continuous monitoring of critical assets

Predictive maintenance

Intelligence at industrial scale

Continuous monitoring of critical assets

Sensors and connected devices are quickly becoming the industry standard. This opens enormous opportunities to create intelligent systems and processes which are run, monitored and managed in an automated environment.

Anomaly detection models can be applied to historic data to learn patterns of normal behavior, then employed in operational monitoring to flag situations where behavior is abnormal.

More time to prevent critical failures

Holistic view to systems and processes

Support maintenance, fleet management and operational functions

Predictive maintenance

True predictive and prescriptive analytics use all available data - current and historic streaming telemetry, environmental data, usage data, inspection and maintenance reports, and more - to accurately and robustly predict failures and their risk at a specific point in time.

Systems based on predictive and prescriptive analytics can be configured to learn continuously. As new data becomes available, representing emergent failure modes due to changes in the operational practices or environment, the models are constantly updated. This closed loop approach is the basis for continuous improvement.

Minimizing downtime and preventing unplanned downtime

Improved quality of product and processes

Improved overall operation of manufacturing and processing plant

Our IoT Solution Platform contains pre-built advanced analytics workflows that encapsulate the acquisition, processing and modeling of data. The infrastructure used to orchestrate and automate the workflow runs as an independently deployable and scalable service in any environment, on-cloud or on-premise.

The pre-built workflows offer businesses a huge productivity asset, a shortcut to low hanging fruit and a springboard towards the long-term efficiencies of mastering the whole data and analytics value chain.

Automated process control

Human-machine collaboration for decision-support

Optimization of e.g. processes, supply chains, production

“Thanks to the headway we have made with the development of the lifecycle model of the roll covering, our customer has been able to extend the servicing interval from five to six weeks. This means substantial direct savings for each roll covering. A single paper machine has from two to ten roll coverings. Production reliability also improves."

Pekka Linnonmaa

Director, Valmet Technologies

Download the Valmet predictive maintenance services case study

We are on a mission to industrialize analytics and power the businesses of today and tomorrow.